Bioinformatic prediction of plant-pathogenicity effector proteins of fungi.

Bioinformatic prediction of plant-pathogenicity effector proteins of fungi.
Curr Opin Microbiol. 2018 Feb 17;46:43-49
Authors: Jones DA, Bertazzoni S, Turo CJ, Syme RA, Hane JK
Abstract
Effector proteins are important virulence factors of fungal plant pathogens and their prediction largely relies on bioinformatic methods. In this review we outline the current methods for the prediction of fungal plant pathogenicity effector proteins. Some fungal effectors have been characterised and are represented by conserved motifs or in sequence repositories, however most fungal effectors do not generally exhibit high conservation of amino acid sequence. Therefore various predictive methods have been developed around: general properties, structure, position in the genomic landscape, and detection of mutations including repeat-induced point mutations and positive selection. A combinatorial approach incorporating several of these methods is often employed and candidates can be prioritised by either ranked scores or hierarchical clustering.
PMID: 29462764 [PubMed - as supplied by publisher]

Source: Current Opinion in Microbiology - February 17, 2018 Category: Microbiology Authors: Jones DA, Bertazzoni S, Turo CJ, Syme RA, Hane JK Tags: Curr Opin Microbiol Source Type: research